RoverS                package:fractal                R Documentation

_E_s_t_i_m_a_t_e _t_h_e _H_u_r_s_t _c_o_e_f_f_i_c_i_e_n_t _b_y _r_e_s_c_a_l_e_d _r_a_n_g_e (_R/_S) _m_e_t_h_o_d

_D_e_s_c_r_i_p_t_i_o_n:

     The series is partitioned into m groups. The R/S statistic is
     computed as described in the references, the number of groups is
     increased, and the calculation is repeated. A log-log plot of R/S
     versus number of groups is, ideally, linear, with a slope related
     to H, so H can be determined by linear regression.

_U_s_a_g_e:

     RoverS(x, n.block.min=2, scale.ratio=2, scale.min=8)

_A_r_g_u_m_e_n_t_s:

       x: a vector containing a uniformly-sampled real-valued time
          series.

n.block.min: minimum number of blocks in partitioning the data. Must be
          at least 2. Default: '2'.

scale.min: minimum number of data values allowed in a block This may be
          restricted so the statistic evaluated within each group is
          from a reasonable sample. Default: '8'.

scale.ratio: ratio of successive scales to use in partitioning the
          data. For example, if 'scale.min=8' and 'scale.ratio=2', the
          first scale will be 8, the second scale 16, the third scale
          32, and so on. Default: '2'.

_V_a_l_u_e:

     estimated Hurst parameter H of the time series.

_R_e_f_e_r_e_n_c_e_s:

     B.B. Mandelbrot and J.R. Wallis (1969), _Water Resources
     Research_, *5*, 228-267.

     See summary in M.S. Taqqu and V. Teverovsky (1998), On Estimating
     the Intensity of Long-Range Dependence in Finite and Infinite
     Variance Time Series, in _A practical Guide to Heavy Tails:
     Statistical Techniques and Applications_, 177-217, Birkhauser,
     Boston.

_S_e_e _A_l_s_o:

     'hurstBlock', 'hurstACVF', 'dispersion'.

_E_x_a_m_p_l_e_s:

     RoverS(ocean)

